Spain

---
title: "Coronavirus (II)"
author: "Rubén F. Bustillo"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
    vertical_layout: fill
    theme: cerulean
---



```{r setup, include=FALSE}

#------------------ paquetes ------------------

devtools::install_github("RamiKrispin/coronavirus")
coronavirus<-coronavirus::coronavirus

library(flexdashboard)
library(coronavirus)
library(tidyverse)
library(echarts4r)
library(DT)
library(plotly)


data(coronavirus)


# COLORES:

# https://www.w3.org/TR/css-color-3/#svg-color

confirmed_color <- "lightsteelblue"
active_color <- "orange"
recovered_color <- "limegreen"
death_color <- "red"



# DATASETS:

# confirmed/active/recovered/death cases by country
df <- coronavirus %>% 
  group_by(Country.Region, type) %>%
  summarise(total = sum(cases)) %>%
  pivot_wider(names_from =  type, 
                     values_from = total) %>%
  mutate(unrecovered = confirmed - ifelse(is.na(recovered), 0, recovered) - ifelse(is.na(death), 0, death)) %>%
  arrange(-confirmed) %>%
  ungroup() %>%
  mutate(country = if_else(Country.Region == "United Arab Emirates", "UAE", Country.Region)) %>%
  mutate(country = if_else(country == "Mainland China", "China", country)) %>%
  mutate(country = if_else(country == "North Macedonia", "N.Macedonia", country)) %>%
  mutate(country = if_else(country == "Dominican Republic", "Dominican Rep.", country)) %>%
  mutate(country = trimws(country)) %>%
  mutate(country = factor(country, levels = country))

df_spain <- df %>%
  filter(country == "Spain")

# CUMULATIVE CASES:

df_daily <- coronavirus %>% 
  group_by(date, type) %>%
  summarise(total = sum(cases, na.rm = TRUE)) %>%
  pivot_wider(names_from = type,
                     values_from = total) %>%
  arrange(date) %>%
  ungroup() %>%
  mutate(active =  confirmed - death - recovered) %>%
  mutate(confirmed_cumulative = cumsum(confirmed),
                death_cumulative = cumsum(death),
                recovered_cumulative = cumsum(recovered),
                active_cumulative = cumsum(active))
  
df1 <- coronavirus %>% 
  filter(date == max(date))


df_map <- df %>%
  mutate(country = recode_factor(country,
                                 `US` = "United States",
                                 `UK` = "United Kingdom",
                                 `UAE` = "United Arab Emirates",
                                 `South Korea`= "Korea"))

```


Spain
=======================================================================


Column
-------------------------------------

### 

```{r, figh.height = 10}

df_Spain <- coronavirus %>% 
  filter(Country.Region == "Spain") %>%
  group_by(date, type) %>%
  summarise(total = sum(cases, na.rm = F)) %>%
  pivot_wider(names_from = type,
              values_from = total) %>%
  arrange(date) %>%
  ungroup()

df_Spain %>%
  datatable(rownames = FALSE)

```

### Confirmed Cases

```{r, fig.width=10, fig.height=10}

plotly::plot_ly(data = df_Spain) %>%
  plotly::add_trace(x = ~ date,
                    y = ~ confirmed,
                    type = "bar",
                    line = list(color = confirmed_color),
                    marker = list(color = confirmed_color)) %>%
  plotly::layout(yaxis = list(title = "Confirmed Cases"),
                 xaxis = list(title = ""))

```

Column 
-------------------------------------
    
### Recovered Cases
    

```{r, fig.width=10, fig.height=10}

plot_ly(df_Spain, 
        x = ~ date, 
        y = ~ recovered, 
        type = "waterfall", 
        increasing = list(marker = list(color = recovered_color, line = list(color = recovered_color, width = 1)))) %>%
  layout(autosize = TRUE)

```  
   
### Death Cases

```{r, fig.width=10, fig.height=10}

plot_ly(df_Spain, 
        x = ~ date, 
        y = ~ death, 
        type = "waterfall", 
        increasing = list(marker = list(color = "red", line = list(color = "red", width = 1))))

``` 
   
Column 
-------------------------------------
   
### confirmed {.value-box}

```{r}

valueBox(value = df_spain$confirmed, 
         caption = "Confirmed Cases in Spain", 
         color = confirmed_color)
```


### active {.value-box}

```{r}

valueBox(value = df_spain$unrecovered, 
         caption = "Active Cases",  
         color = active_color)
```

### recovered {.value-box}

```{r}

valueBox(value = df_spain$recovered, 
         caption = "Recovered Cases", 
         color = recovered_color)
```

### death {.value-box}

```{r}

valueBox(value = df_spain$death,
         caption = "Death Cases", 
         color = death_color)

```